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Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more
Transformers 3rd Edition
The purpose of this repository is to introduce new dialogue-level commonsense inference datasets and tasks. We chose dialogues as the data source because dialogues are known to be complex and rich in commonsense.
A quantitative study on over 1.25 million tweets about ChatGPT, employed data scrapping, data cleaning, EDA, topic modeling, and sentiment analysis.
NLP model zoo for Russian
Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.
PyTorch implementation of Sentiment Analysis of the long texts written in Serbian language (which is underused language) using pretrained Multilingual RoBERTa based model (XLM-R) on the small dataset.
Sentiment Analysis of tweets written in underused Slavic languages (Serbian, Bosnian and Croatian) using pretrained multilingual RoBERTa based model XLM-R on 2 different datasets.
This app Classifies the text generated by AI tools like chatGPT. Roberta-base-openai-detector Model has been used from hugging face to detect ai generated texts.
This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.
This is a project of twitter sentiment analysis using machine learning(Support Vector Machines,Naive Bayes), deep learning(LSTM), Transformer(BERT,ROBERTA).
Convert pretrained RoBerta models to various long-document transformer models
CatIss is an intelligent tool for automatic categorization of issue reports based on the RoBERTa model.
It is the nlp task to classify empathetic dialogues datasets using RoBERTa, ERNIE-2.0 and XLNet with different preprocessing method. You can get some detailed introduction and experimental results in the link below.
NLP (Natural Language Processing)
Train a T5 model to generate simple Fake News and use a RoBERTa model to classify what's fake and what's real.
Key Point Analysis: implementation of two-component system for performing Key Point Matching and Key Point Generation task with multiple PLMs.
Code repository for the paper: How Much Hate with #china? A Preliminary Analysis on China-related Hateful Tweets Two Years After the Covid Pandemic Began
This repository contains the solutions to three problem statements completed during the hackathon. Each problem statement is categorized based on its difficulty level: Easy, Moderate, and Hard.
Building this project to generate MCQ Questions from any type of text and generate answers and distractors for it.
Resources for the paper: Monolingual Pre-trained Language Models for Tigrinya
Tutorial on training a RoBERTa Transformers model from scratch
Compute RoBERTa embeddings in PHP using ONNX framework.
An NLP Java Application that detects Names, organizations, and locations in a text by running Hugging face's Roberta NER model using ONNX runtime and Deep Java Library.
This work focuses on the development of machine learning models, in particular neural networks and SVM, where they can detect toxicity in comments. The topics we will be dealing with: a) Cost-sensitive learning, b) Class imbalance
Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language. Natural language processing has the ability to interrogate the data with natural language text or voice.
LayoutLMv3 applied to a VQA problem with infographics.
🙂🙃 Being happy :) being sad :( with this tool, you become sentiment GIGA chad!
Generating code with Ludwig AI/ML (PyTorch, Tensorflow)
Building a multilingual NER app with HuggingFace, Gradio and Comet
This repository contains assignments, the final course project, and the project work assigned for the Natural Language Processing (NLP) course within the Artificial Intelligence Master's program.